Module 2: SQL for Analysis
Module Overview
SQL is simple, but can still be surprisingly powerful - as we learned in the first unit, a lot of analysis can be done with just descriptive statistics, and with the right query SQL can do all that and more.
Learning Objectives
- Deploy and connect to a managed PostgreSQL database
- Use CREATE and INSERT statements to make tables, set their schema, and add rows to them
- Create a data pipeline with SQL
Guided Project
Important Note
The following Guided Project demonstrates using a cloud PostgreSQL service called ElephantDB, which has since stopped taking new sign ups, to accomplish the project's objectives.
In order to follow along, some adjustments must be made:
- Use Aiven.io instead of ElephantDB as demonstrated in Learning Objective 1 in this module.
- Connect to and interact with your database from your Python code as demonstrated in Learning Objective 2.
In this guided project, we'll learn how to deploy PostgreSQL databases and use SQL for data analysis. Open guided-project.md in the GitHub repository below to follow along with the guided project.
Module Assignment
Important Note
The following Module Assignment demonstrates using a cloud PostgreSQL service called ElephantDB, which has since stopped taking new sign ups, to accomplish the project's objectives.
In order to follow along, some adjustments must be made:
- Use Aiven.io instead of ElephantDB as demonstrated in Learning Objective 1 in this module.
- Connect to and interact with your database from your Python code as demonstrated in Learning Objective 2.
For this assignment, you'll practice deploying a PostgreSQL database, creating tables, and building data pipelines using SQL for analysis.